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Computational Modeling Simulation Multiphysics Jobs in Alexandria, VA

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

Senior Nuclear Engineer

Reston, VA · On-site

$102K - $122K/yr

... multiphysics modeling and simulation tools to evaluate structural, thermal, and electronic degradation of nuclear-related facilities and processes exposed to weapons effects. * Perform computational ...

Senior Nuclear Engineer

Reston, VA · On-site

$102K - $122K/yr

... multiphysics modeling and simulation tools to evaluate structural, thermal, and electronic degradation of nuclear-related facilities and processes exposed to weapons effects. * Perform computational ...

SIERRA Modeling and Simulation (M&S) Subject Matter Expert (SME) Location: Reston, VA Clearance ... The ideal candidate will have a strong academic background in computational fluid dynamics (CFD ...

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Computational Modeling Simulation Multiphysics information

See Alexandria, VA salary details

$41.7K

$108.4K

$154.1K

How much do computational modeling simulation multiphysics jobs pay per year?

As of Jul 14, 2026, the average yearly pay for computational modeling simulation multiphysics in Alexandria, VA is $108,375.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $138,600.00 per year, depending on experience, location, and employer.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What are the key skills and qualifications needed to thrive as a Computational Modeling Simulation Multiphysics Engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What are some common challenges faced by professionals in Computational Modeling Simulation Multiphysics roles, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.
What are popular job titles related to Computational Modeling Simulation Multiphysics jobs in Alexandria, VA? For Computational Modeling Simulation Multiphysics jobs in Alexandria, VA, the most frequently searched job titles are:
What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Alexandria, VA look for? The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Alexandria, VA are:
What cities near Alexandria, VA are hiring for Computational Modeling Simulation Multiphysics jobs? Cities near Alexandria, VA with the most Computational Modeling Simulation Multiphysics job openings:
Infographic showing various Computational Modeling Simulation Multiphysics job openings in Alexandria, VA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $108,375 per year, or $52.1 per hour.
Term Assistant Professor, Computational and Data Sciences

Term Assistant Professor, Computational and Data Sciences

George Mason University

Fairfax, VA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


George Mason University rating

8.3

Company rating: 8.3 out of 10

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Job description

Term Assistant Professor, Computational and Data Sciences
  • 10003730
  • Fairfax, VA
  • Instructional Faculty
  • Opening on: Feb 9 2026
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Department: College of Science

Classification: 9-month Instructional Faculty

Job Category: Instructional Faculty

Job Type: Full-Time

Work Schedule: Full-time (1.0 FTE, 40 hrs/wk)

Location: Fairfax, VA

Workplace Type: Hybrid Eligible

Sponsorship Eligibility: Not eligible for visa sponsorship

Salary: Salary commensurate with education and experience

Criminal Background Check: Yes

Works with Minors check: Yes

About the Department:

The Department of Computational and Data Sciences (CDS) (https://sciences.gmu.edu/cds) at George Mason University (GMU) is a rapidly growing department for data science and computing innovation. Part of the College of Science, CDS advances state-of-the-art research and delivers top-tier education at both undergraduate and graduate levels.

The Department offers a Bachelor of Science in Computational and Data Science. This program integrates data analytics, modeling, and scientific computing to prepare students for careers in industry, government, and beyond. CDS provides career advancement opportunities for graduate students through its M.S. in Computational Science, Ph.D. in Computational Sciences and Informatics, and Ph.D. in Computational Social Science. These programs emphasize technical expertise and the interdisciplinary applications of computation, modeling & simulation, and data-driven discovery.
Complementing its educational mission, CDS faculty develop, conduct, and disseminate cutting-edge, externally funded interdisciplinary research in diverse application areas where computational science, data science, and modeling & simulation are essential. Its recent research portfolio includes funding from the National Science Foundation (NSF), Defense Threat Reduction Agency (DTRA), Central Intelligence Agency (CIA), Intelligence Advanced Research Projects Activity (IARPA), Department of Homeland Security (DHS), and the U.S. Department of the Army.
Through collaborations with government and industry partners at both regional and national levels, the department strives to ensure its research remains competitive. In alignment with the broader mission of GMU and the College of Science, CDS is also strongly committed to engagement, working with high school, undergraduate, and graduate students, as well as stakeholder communities through research opportunities, internships, summer programs, and collaborations within and beyond the university.
George Mason University College of Science (Mason Science) is committed to advancing inclusive excellence and fostering an environment free from discrimination, harassment, and retaliation throughout our STEM community. At Mason Science, our values include cultivating an organizational culture that promotes belonging, respect, and civility. We believe that varied opinions, cultures, and perspectives are what provides vibrancy, innovation, and growth to an academic community. By prioritizing cultural responsiveness in academics, teaching, research, and global engagement, we strive to attract faculty and staff who exemplify the Mason Science mission and vision.

About the Position:

The position in the Department of Computational and Data Sciences (CDS) will support the department's efforts to achieve its mission in education and engagement. The successful Term Assistant Professor is expected to: (a) teach at both the undergraduate and graduate levels, develop new course curriculum, and support the department's undergraduate, certificate, Master, and two PhD programs; and (b) participate and contribute to service at the department, college, university, and relevant scientific communities/organizations, as well as support department activities to promote its programs.

Responsibilities:

  • Teach courses offered by CDS at the undergraduate and graduate levels in all course modalities (in-person, hybrid, and fully online) as assigned, develops new courses in area(s) of expertise, and supports teaching activities across undergraduate, certificate, and graduate programs in the department; holds office hours, mentors students, and supervises graduate and undergraduate student research, which may also include the oversight of GTAs, GRAs and department Student Teachers and Research (STAR) Assistants.
  • Service to the department, college, and university: serves on department standing and ad-hoc committees, supports department efforts to grow and promote the department and its programs, and serves on college- and university-level committees appropriate for career stage and experience.

Required Qualifications:

  • Doctoral degree in a closely related field including Data Science, Information Science, Scientific Computing, Computational Science, Artificial Intelligence, Simulation, or Modeling is required prior to starting this appointment;
  • One year of experience teaching at the undergraduate level as a teaching assistant or instructor of record;
  • Demonstrated commitment to ethics and professional values;
  • Knowledge and skills in developing, delivering, and maintaining high quality curriculum and instruction at the undergraduate level in the following areas: data science foundations, data science ethics, scientific computing, and artificial intelligence;
  • Ability to mentor undergraduate and graduate students and guide students in their academic and professional growth;
  • Knowledge for and ability to develop new courses in one of more fields of specialization;
  • Ability to communicate with students, faculty, and staff effectively; and
  • Strong interpersonal skills to build professional relationships with students, faculty, and staff.

Preferred Qualifications:

  • Demonstrated record of excellence in teaching at the undergraduate level;
  • Two or more years of experience teaching at the undergraduate level as a teaching assistant or instructor of record;
  • Two or more years of experience working in a computational and data sciences field in an industry or government setting;
  • Experience teaching multi-section courses and large courses;
  • Demonstrated teaching record that combines Artificial Intelligence and/or Machine Learning with one or more of the following areas: Scientific Computing, Modeling, Simulation, Scientific Visualization, or Computational Social Science;
  • Experience developing and maintaining course curriculum and materials;
  • Experience developing and/or implementing innovative teaching and student engagement methods;
  • Experience with a variety of technical environments commonly used in computational science and data science, including relevant software and hardware;
  • Strong knowledge and familiarity with the foundation and state-of-the-art in modeling and simulation, databases, data visualization, and high-performance computing;
  • Knowledge in other areas that align with or strongly complement those of the department curriculum;
  • Knowledge of best practices for developing and delivering course curriculum;
  • Outstanding verbal and written communication skills;
  • Excellent organizational and time management skills;
  • Ability to work and collaborate effectively in group settings;
  • Ability to work and collaborate effectively in interdisciplinary groups; and
  • Commitment to mentoring and educating a broad range of students, particularly those who are traditionally underrepresented in STEM.

Instructions to Applicants:

For full consideration, applicants must apply for the Term Assistant Professor, Computational and Data Sciences at https://jobs.gmu.edu/. Complete and submit the online application to include three professional references with contact information, and provide a letter of intent, CV, philosophy of teaching, and an unofficial copy of transcript (required only for candidates with less than 2 years of post-PhD experience).

Posting Open Date: February 9, 2026

For Full Consideration, Apply by: March 9, 2026

Open Until Filled: Yes


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